Marcella Simoes

Leading global data engineering teams across platform modernization and data product / AI enablement. Currently empowering our Specialized Portfolio businesses - Animal Nutrition & Health, Bioindustrial, Road Safety (Deicing).

• Led enterprise data product and engineering enablement by establishing standards, frameworks, and reference architectures that governed how data products were designed, built, and consumed across business segments. • Defined and operationalized reusable engineering accelerators and lifecycle practices, enabling scalable, consistent delivery of governed data assets. • Served on the Architecture Review Board, providing oversight on data architecture decisions, ensuring alignment with enterprise patterns, and influencing long-term technical direction. • Partnered with architecture, platform, governance, delivery, and business teams to align data product design with enterprise priorities and downstream consumption needs. • Ensured data foundations were AI-ready, supporting adoption of advanced capabilities (e.g., AI/ML, graph analytics) through reliable, reusable pipelines and disciplined engineering practices. • Supported global engineering teams through enablement and standards adoption, improving consistency, clarity of ownership, and delivery efficiency.

• Led a global BI and data engineering team supporting the Cellulose business, delivering ERP-integrated, cloud-based analytics platforms used across multiple markets. • Owned end-to-end BI platform delivery, including data pipelines, semantic models, and performance optimization to enable reliable, scalable self-service analytics. • Partnered with business and IT leaders to align analytics solutions with operational and financial KPIs, ensuring consistency, adoption, and trust in reported results. • Established delivery and support practices that improved data reliability, refresh performance, and user confidence across reporting and analytics solutions.

• Developed and deployed thousands of pipelines supporting critical enterprise functions. • Designed data lakes, warehouses, and marts to enable consistent, high-quality analytics. • Introduced reusable engineering patterns that accelerated adoption of modern platforms.

• Engineered real-time and batch ingestion pipelines with AWS Glue, Kinesis, and Spark. • Designed high-availability storage and retrieval on AWS S3 and Redshift. • Optimized workflows with serverless services (Lambda, Glue, S3) to reduce cost and increase scalability.

• Prototyped reporting solutions and visualizations to support analytics and decision-making in higher education.

• Advanced expertise in data engineering, BI, and analytics through graduate studies, applied projects, and certifications (M.S. in IT, Graduate Certificate in Data Analytics & Intelligence, AWS, Azure, Power BI). • Also served in professional roles outside of technology, including as a Consular Agent at the Consulate of Brazil, where I managed sensitive information and supported administration, stakeholder engagement, and cross-cultural communication — reinforcing skills in confidential data handling and process integrity.

• Taught advanced physics, materials science, calculus, and programming (Python, SQL) to engineering undergraduates. • Mentored students in analytical thinking and applied computing, strengthening leadership and communication skills. • Built a strong foundation in mathematical modeling and problem-solving that informs modern data engineering leadership.

• Conducted research in machine learning and optimization algorithms, publishing a book chapter and peer-reviewed papers. • Designed and tested algorithms with applications in computational intelligence, building early AI/ML expertise. • Developed a mindset of innovation, experimentation, and applied problem-solving that underpins current AI/ML enablement.